The technology instrumental in predictive maintenance includes sensors, data analytics, and machine learning algorithms. These tools enable organizations to monitor equipment performance in real-time and predict potential failures before they occur. By analyzing data collected from various sources, predictive maintenance helps identify patterns and anomalies that indicate wear or malfunctions. This proactive approach reduces downtime, extends the lifespan of assets, and optimizes maintenance schedules, ultimately lowering operational costs and improving overall equipment effectiveness.